AI Engineering Lead -Marketing & Personalization
Job Overview
Proudly voted a Great Place to Work®, we are a dynamic startup in the SaaS space that is revolutionizing the way businesses communicate. Our team is made up of 500 energetic and passionate Unifones who are dedicated to delivering the best possible experience to 5000+ customer-centric companies.
We pride ourselves on our fun and collaborative work environment, where creativity and new ideas are constantly encouraged. As shareholders in the business, we’re so much more than a group of passionate communicators. We are Unifones. Join our team and be a part of something big!
Meet the team!
The Marketing & Personalization Squad partners with Product, Data and Marketing to ship real‑time recommendations and predictive insights that lift conversion, retention and lifetime value.
As a Machine Learning Tech Lead – Marketing & Personalization, you will draw on deep, hands-on experience in delivering production-grade recommendation & personalization AI solutions. This role is ideal for someone who has "been there and done that" in building and scaling large-scale personalization and recommendation systems deployed to millions of users in production. You will own the end-to-end personalization platform, from data pipelines to real-time inference APIs, lead a lean, senior team, and rapidly deliver measurable commercial outcomes hands-on.
Help us shape the future of communication by:
Defining the technical roadmap, architecture, and coding standards.
Building and operating batch, near‑real‑time and streaming pipelines using systems such as Spark, Airflow, Kafka or RabbitMQ.
Training, evaluating, and deploying models for recommendations, segmentation, churn, conversion, and CLV.
Serving models through API, containerized with Docker, orchestrated on Kubernetes, and fully automated via CI/CD, with excellent performance and following best software engineering/architecture principles, ideally with Java but also possible in Python.
Maintaining high‑volume, low‑latency storage and caching with technologies like MySQL, Cassandra, Redis or Memcached.
Embedding ML observability, A/B testing, and KPI tracking in every release.
Upholding GDPR and Saudi PDPL compliance and championing responsible AI.
· Hiring, coaching and inspiring engineers; running design and code reviews; fostering a culture of clean architecture and SOLID principles.